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For Companies At a Glance
- Tasks: Transform complex data into insights and models that drive business decisions.
- Company: Established FinTech company revolutionising global money management.
- Benefits: Competitive salary, 25 days holiday, private healthcare, and a learning budget.
- Why this job: Shape the future of AI and machine learning in a dynamic environment.
- Qualifications: Strong statistical modelling, Python skills, and experience with ML models.
- Other info: Flexible hybrid working and excellent career growth opportunities.
The predicted salary is between 42000 - 84000 £ per year.
We're working with an established FinTech / Payments business that has been helping customers manage and move money globally for many years. The company builds technology-led products that support low-cost, multi-currency payments and money management, operating across several regulated markets.
They're now investing further in their Data Science and AI capability and are looking for a Data Scientist to play a key role in shaping how advanced analytics, machine learning and AI are used across the business.
The role involves turning complex datasets into meaningful insights and production-ready models that influence real business decisions. You'll partner closely with Product, Engineering and Analytics teams, helping to identify where data science and machine learning can add the most value. This role combines hands-on technical work with the opportunity to influence strategy, tooling and ways of working, particularly around AI and ML adoption. You'll be involved across the full lifecycle, from problem definition and experimentation through to deployment, governance and ongoing optimisation.
What you’ll be doing:
- Leading the use of advanced analytics, machine learning and AI within the data team
- Collaborating with Product and Engineering on strategic AI-driven initiatives
- Identifying and developing high-impact use cases for data science and ML
- Helping define ML lifecycle standards, documentation and governance
- Communicating insights and model outputs clearly to technical and non-technical stakeholders
What we’re looking for:
Essential experience:
- Strong grounding in statistical modelling, experimentation and inference
- Advanced Python skills (NumPy, pandas, scikit-learn, PyTorch or TensorFlow)
- Experience building, deploying and optimising ML models in production
- Strong AWS experience (e.g. SageMaker, Lambda or similar services)
- Expert SQL skills and experience working with large, complex datasets
- Solid data engineering fundamentals, including pipelines and APIs
- Comfortable with MLOps practices such as CI/CD, containerisation and monitoring
- Clear, pragmatic communicator who works well across teams
Nice to have:
- Experience with agentic or LLM-based frameworks
- Exposure to causal inference, uplift modelling or advanced experimentation
- Experience working in fintech or another regulated environment
- Awareness of data governance, privacy and model ethics
What’s on offer:
- Competitive salary with flexibility for the right profile
- 25 days holiday plus an additional day off
- Annual learning and development budget
- Private healthcare and wellbeing support
- Pension, life assurance and additional benefits
- Hybrid working with flexibility where possible
This role would suit someone who enjoys working on real-world data problems, wants to influence how AI and machine learning are used responsibly in production, and is looking for a role with both technical depth and business impact.
If you’re interested, apply directly or reach out for a confidential conversation.
Data Scientist in Swindon employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Swindon
✨Tip Number 1
Network like a pro! Reach out to people in the FinTech space, especially those working with data science. Use LinkedIn to connect and engage with them; you never know who might have a lead on that perfect Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and AI. This is your chance to demonstrate how you can turn complex datasets into actionable insights, just like the job requires.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of statistical modelling. Be ready to discuss your experience with Python, AWS, and SQL, as these are key for the role. Practice explaining your past projects clearly to both technical and non-technical folks.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to reach out directly for a chat about their fit for the role.
We think you need these skills to ace Data Scientist in Swindon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with statistical modelling, Python, and ML models. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Don't forget to mention any relevant projects or experiences that showcase your skills.
Showcase Your Projects: If you've worked on any cool data science projects, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they involve machine learning or AI!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Thyme
✨Know Your Data Science Stuff
Make sure you brush up on your statistical modelling and machine learning concepts. Be ready to discuss your experience with Python libraries like NumPy and pandas, as well as any projects where you've built or optimised ML models. This is your chance to show off your technical skills!
✨Showcase Your Collaboration Skills
Since the role involves working closely with Product and Engineering teams, think of examples where you've successfully collaborated across different departments. Highlight how you communicated complex data insights to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between tech and business.
✨Prepare for Real-World Scenarios
Expect questions that ask you to solve real-world data problems. Practice explaining your thought process when defining problems, experimenting, and deploying models. Being able to articulate your approach to MLOps practices will also set you apart from other candidates.
✨Understand the FinTech Landscape
Familiarise yourself with the FinTech industry, especially around payments and data governance. Knowing the challenges and regulations in this space will help you speak confidently about how you can contribute to the company's goals and ensure responsible AI usage.
